Auto-regression - Reduce error in prediction
The predictions tend to move towards the mean of the series as one predicts for longer horizons. Also, in general, optimal long range forecast is the process mean.

In other words, the past of the process contains no information on the development of the process in the distant future.

And, this might be the reason that you are getting poor forecasts. 


  What changes should be done in the approach? or Do I have to change the model?


You might want to move to ARIMA models. See how they perform. 

If you have some other time series that might act as explanatory variables then you might want to augment the dataset and use the ARIMAX model. 

Third option would be to try out RNN if you have lots of data. You can also try hybrid models like ARIMA and RNN together.